The present invention relates to a space segmentation method for 3D point clouds, and more particularly to a space segmentation method for 3D point clouds so as to segment 3D point clouds from large-scale scanning into a plurality of spatially-meaningful groups.
Scanner devices have been widely used in various fields so as to quickly obtain correct 3D data.
Data obtained through the scanner device is called 3D point clouds. A variety of techniques for handling point clouds have been intensively.
The problem of segmenting 3D point clouds is considered to be the most principal and difficult problem, because real-world data obtained by the scanner device includes a large amount of noise. Because of noise, it is difficult to accurately discriminate a boundary between background data and an object.
The related art of the present invention has been disclosed in Korean Patent Laid-open Publication No. 10-2010-0106126 (published on Oct. 1, 2010).